Metabolomics analysis reveals metabolite changes during freeze-drying and oven-drying of Angelica dahurica

Angelica dahurica (Angelica dahurica Fisch. ex Hoffm.) is widely used as a traditional Chinese medicine and the secondary metabolites have significant pharmacological activities. Drying has been shown to be a key factor affecting the coumarin content of Angelica dahurica. However, the underlying mechanism of metabolism is unclear. This study sought to determine the key differential metabolites and metabolic pathways related to this phenomenon. Liquid chromatography with tandem mass spectrometry (LC–MS/MS) based targeted metabolomics analysis was performed on Angelica dahurica that were freeze-drying (− 80 °C/9 h) and oven-drying (60 °C/10 h). Furthermore, the common metabolic pathways of paired comparison groups were performed based on KEEG enrichment analysis. The results showed that 193 metabolites were identified as key differential metabolites, most of which were upregulated under oven drying. It also displayed that many significant contents of PAL pathways were changed. This study revealed the large-scale recombination events of metabolites in Angelica dahurica. First, we identified additional active secondary metabolites apart from coumarins, and volatile oil were significantly accumulated in Angelica dahurica. We further explored the specific metabolite changes and mechanism of the phenomenon of coumarin upregulation caused by temperature rise. These results provide a theoretical reference for future research on the composition and processing method of Angelica dahurica.

The identification of metabolites of Angelica dahurica. The mass spectral data were processed using the software Analyst 1.6.3. The metabolites of the samples were qualitatively and quantitatively analyzed by mass spectrometry based on the local metabolic database. As shown in the figure (Supplementary fig. S2), the MRM metabolite detection peak map (multi-substance extracted ion chromatogram, XIC). It shows the substances that can be detected in the sample, and each mass spectrum peak of different colors represents a detected metabolite. The characteristic ions of each substance are screened out by triple quadrupole, the signal intensity (CPS) of the characteristic ions is obtained in the detector, the mass spectrum file of the sample is opened with MultiaQuant 3.0.3 software, and the integration and correction of chromatographic peaks are carried out. The peak area (Area) of the peak represents the relative content of the corresponding substance. Finally, all chromatographic peak area integration data are exported and saved.
The cluster heatmap of metabolites in all samples is displayed in Fig. 2B. Some metabolites of Angelica dahurica were upregulated when treated in a drying oven but downregulated in a lyophilizer, suggesting significant differences in metabolites between oven-drying and freeze-drying treatment. The up regulation of 'content' is not an absolute increase or decrease, but a relative increase or decrease. During the screening of differential metabolites, if the grouping information is A vs B, it means that A is the control group and B is the experimental group for data analysis. If the final screening of differential metabolites is up-regulated, it means that the content of metabolite is relatively low in A, and relatively high in B. Four main clusters were obtained. Clusters 1 and 2 accumulated at high levels in TYD and TJXD. Clusters 3 and 4 accumulated at high levels in TYH and TJXH. Moreover, the three biological replications of each group were clustered together, indicating a good homogeneity between duplicates and the high reliability of the data.
Widely targeted metabolite analysis based on OPLS-DA. OPLS-DA analysis is a multivariate statistical analysis with supervised pattern recognition, which can effectively eliminate irrelevant effects to screen differential metabolites. In the OPLS-DA score plot (Fig. 3C), the TYD samples were distributed on the left side of the confidence interval, while the TYH samples were distributed on the right. The core value of the principal component in the OSC process (T score [1]) was 76.8%. The orthogonal T score [1] in the OSC process was 5.49%. The prediction parameters of the evaluation model are R 2 X, R 2 Y and Q 2 . R 2 X and R 2 Y represent the interpretation rate of the X and Y matrices of the built model respectively, and Q 2 represents the prediction ability of the model. The closer these three indicators are to 1, the more stable the model is. During model verification (n = 200, that is, 200 permutation experiments) of OPLS-DA (Fig. 3D), Q 2 = 0.994 > 0.9, R 2 Y = 1, R 2 X = 0.822, P < 0.005. Similarly, in another OPLS-DA score plot (Fig. 3A), the TJXD and TJXH samples were clearly separated and during model verification (Fig. 3B), Q 2 = 0.98 > 0.9, R 2 Y = 1, R 2 X = 0.743, P < 0.005 further indicated that two models were both reliable.
Analysis of metabolites variations for Angelica dahurica derivative from two plantation bases under two drying methods. The differential metabolites of TYD vs. TYH and TJXD vs. TJXH were initially screened using OPLS-DA. The fold change value and VIP value were used comprehensively to screen the differential metabolites. Metabolites with a fold change ≥ 2, a fold change ≤ 0.5, and a VIP ≥ 1 were selected as significant differential metabolites. The volcano plot in Fig. 4A,B suggest a significant difference in differential metabolites, which further validated the reliability of the results. For TJXD vs. TJXH, 258 (210 upregulated and 48 downregulated) differential metabolites were obtained. For TYD vs. TYH, 417 (264 upregulated and 153 downregulated) were identified as differential metabolites. As shown in Supplementary Fig. S1, for both groups, www.nature.com/scientificreports/ more metabolites were upregulated under oven drying than freeze-drying, indicating that physiological and biochemical reactions were promoted by oven drying. As shown in Supplementary Table S1, the metabolites for TJXD vs. TJXH selected metabolites were classified into 10 major classes and 28 subclasses, including amino acids and derivatives (n = 27), phenolic acids (n = 45), nucleotides and derivatives (n = 32), flavonoids (n = 13), lignans and coumarins (n = 12), alkaloids (n = 24), Terpenoids (n = 4), organic acids (n = 24), lipids (n = 55) and others (n = 22). The metabolites for TYD vs. TYH selected were classified into 10 major categories and 36 subcategories, including amino acids and derivatives (n = 32), phenolic acids (n = 63), nucleotides and derivatives (n = 49), flavonoids (n = 51), quinones (n = 1), lignans and coumarins (n = 28), alkaloids (n = 44), terpenoids (n = 8), organic acids (n = 32), lipids (n = 55) and others (n = 34). Our results suggest more types of differential metabolites in TY than in TJX, especially alkaloids and flavonoids, which may be attributed to the different plantation bases.
Identification of common differential metabolites of two plantation bases. The successful identification of common differential metabolites could assist in figuring out the physiological and biochemical reactions of Angelica dahurica during drying. We combined and filtered these data based on the two sets of differential metabolites mentioned previously. 193 common differential metabolites were obtained between both groups (Supplementary Table S2). Among these differential metabolites, 158 were upregulated, and 35 were www.nature.com/scientificreports/ downregulated, implying that some key physiological metabolites and metabolic activities might be activated during oven drying. These metabolites were classified into 10 major classes and 24 subclasses, including amino acids and derivatives (n = 25), nucleotides and derivatives (n = 32), phenolic acids (n = 32), flavonoids (n = 12), lignans and coumarins (n = 7), alkaloids (n = 21), organic acids (n = 21), lipids (n = 25), terpenoids (n = 1) and others (n = 13). Among these metabolites, amino acids and derivatives, nucleotides and derivatives, lipids and organic acids were the primary plant metabolites, while phenolic acids, flavonoids, lignans and coumarins, alkaloids and terpenoids were the secondary metabolites. As shown in Fig. 5, these differentially expressed metabolites were concentrated in amino and derivatives, phenolic acids, nucleotides and derivatives, and organic acids. Pairwise comparisons showed that the number of upregulated metabolites was significantly higher than downregulated metabolites. Moreover, the number of secondary metabolites was higher during oven drying than freezedrying, which indicated that the physiological and biochemical reactions of Angelica dahurica under heat were similar to Angelica dahurica under biological or abiotic stress. In addition, seven lignans and coumarins were all upregulated during oven drying, consistent with the literature. www.nature.com/scientificreports/ KEGG annotation and enrichment analysis of differential metabolites. All differential metabolites in pairwise comparison groups were matched to the KEGG database (www. kegg. jp/ kegg/ kegg1. html.) to obtain the metabolic pathway information. KEGG annotation and enrichment analysis were conducted, and the enriched pathways are shown in Fig. 6A,B. For TJXD vs. TJXH, the enriched metabolic pathways of these differential metabolites consisted of tyrosine metabolism, tryptophan metabolism, pyrimidine metabolism, purine metabolism, phenylpropanoid biosynthesis, phenylalanine metabolism, and linoleic acid metabolism. For TYD vs. TYH, the enriched pathways of differential metabolites contained pyrimidine metabolism, purine metabolism, phenylalanine metabolism, lysine degradation and glutathione metabolism. The intersection yielded pyrimidine, purine, and phenylalanine metabolism as significantly enriched pathways for these differential metabolites. Purine and pyrimidine metabolism are involved in the synthesis of precursor materials that are essential for downstream synthesis. Specifically, purine and pyrimidine bases are produced during purine and pyrimidine metabolism and are basic materials for the synthesis of nucleotides. Nucleotides are essential   www.nature.com/scientificreports/ cellular components that play an important role in plant growth, development, metabolism, and synthesis of other substances. Moreover, purine and pyrimidine metabolism is required for primary and secondary plant metabolism 13,14 . For instance, uridine diphosphate (UDP) (Compound CID: 6031) was produced during the pyrimidine metabolism (Fig. 6C). Under the catalysis of sucrose synthase, sucrose and UDP reacted reversibly to produce fructose and UDP glucose. UDP-glucose acted as a glucosyl donor in the derivatization of secondary metabolites and hormones in a wide range of reactions catalyzed by the enormous protein family of UDPglucose glycosyltransferases. Xanthosine (Compound CID: 64959) was produced during the purine metabolism, participating in the synthesis of alkaloids such as theobromine, caffeine and so on (Supplementary table S4). Phenylalanine metabolism is one of the most crucial pathways for secondary metabolite synthesis in plants. We found that phenolic acids, flavonoids, lignans and coumarins and some alkaloids were synthesized by this pathway (Fig. 6C). Phenylalanine (Compound CID: 6140) was synthesized by shikimic acid (Compound CID: 8742). Under the action of phenylalanine ammonia-lyase (PAL), phenylalanine is converted to trans-cinnamic acid (Compound CID: 139054223). Then trans-cinnamic acid was transferred to P-coumaric acid (Compound CID: 637542) under the action of cinnamate 4-hydroxylase (C4H) (Supplementary Table S4). Trans cinnamicacid serves as the most important precursor substance of secondary metabolites. PAL and C4H are also considered two core enzymes.

Discussion
At present, research on the composition of Angelica dahurica has mainly focused on coumarin and volatile oil. In this study, we used widely-targeted metabolomics 15 which is well-established for its high sensitivity, accurate quantitative and qualitative properties, and wide coverage to identify metabolites of Angelica dahurica in two plantation bases following two distinct drying methods. Compared with other researches about the effects of www.nature.com/scientificreports/ different drying methods on the quality of Angelica dahurica, we used freeze drying as the control group and oven drying as the experimental group to reveal the differential metabolites produced under the two drying methods, aiming to explore the coumarin changes in Angelica dahurica with temperature from the perspective of metabolism. We screened 995 metabolites, of which 27 were in the top 50 in each of the four groups (Supplementary  Table S3). Most secondary metabolites belonged to the coumarin class except for the primary metabolites, which maintain the organism's normal activities. Other classes of secondary metabolites were identified. For example, pterolactam (Compound CID: 181561), isolated from Chrysanthemum coronarium L. and rhizome of Coniogramme japonica, has been classified in pyrrole alkaloids and recent studies have shown that it has antimicrobial activity. Anca-Elena Dascalu et al. evaluated Pterolactam's antifungal activities on a panel of nine fungal strains and three non-albicans candida yeast species [16][17][18] . L-Pipecolic acid (Compound CID: 439,227) is an intermediate of L-Lysine catabolism, and its central injection is reported to exert a hypnotic effect on the brain 19 . Moreover, it plays an important role in medical issues, rhizosphere ecology, decontamination of polluted soils, nutrient acquisition and plant resistance [20][21][22][23] . At the same time, besides coumarin and volatile oil in Angelica dahurica, there were still some other secondary metabolites with high content, pharmacological effects and application value. This study provides a theoretical reference for future research on other substances in Angelica dahurica (Supplementary table S4). It has been established that widely-targeted metabolome analysis enables the quantitative detection of approximately a thousand metabolites at a time, conducive to the comprehensive and effective comparison of metabolite differences and analysis of metabolic pathways 24 . Differential metabolite analysis yielded 193 differential metabolites classified into 10 major classes. Among these differential metabolites, 158 were upregulated, and 35 were downregulated. In lipids, fatty acids were upregulated, but glycerol ester consisting of linoleate and linolenate was downregulated. The increase in the saturation level of fatty acids has positive effects on maintaining membrane stability and heat tolerance, given that a greater proportion of saturated fatty acids might result in a higher lipid melting temperature and prevent a heat-induced increase in membrane fluidity 25 . Linoleate and linolenate are the major fatty acids in plant membranes 26 . Therefore, we speculate that with an increase in processing temperature, linoleate and linolenate content would be decreased after the cell membrane of Angelica dahurica was damaged, while an increase in fatty acid content could prevent increased membrane fluidity caused by heat. In addition, coumarin was upregulated, consistent with the literature. Based on the KEGG annotation and enrichment results, three metabolic pathways were mapped to these overlapping differential metabolites, namely pyrimidine metabolism, purine metabolism and phenylalanine metabolism. Given that purine and pyrimidine metabolism participate in the synthesis of upstream substances, we discussed the phenylalanine metabolism pathway next.
The biosynthesis pathway of phenylpropanoid, one of the major secondary metabolites in plants under abiotic or biotic stress, is reported to generate numerous antioxidants, including flavonoids, lignans, and phenols, to protect plants from being attacked 27,28 . UV-C irradiation has been found to increase phenylpropanoid pathway gene expression in sweet cherries (Prunus avium L.) 29 . In this study, phenylpropanoid biosynthesis was significantly enhanced with increased temperature. In phenolic acids, the first and second metabolites and their derivatives of phenylalanine were increased, such as cinnamic acid, p-coumaric acid, p-coumaraldehyde, p-coumaryl alcohol, hydrocinnamic acid, 2-hydroxycinnamic acid, and 4-methoxycinnamic acid which substantiated the activation of phenylalanine pathway and provided precursor substances for the increase of flavonoids, coumarin, lignin. It is possibly associated with the activation of PAL and C4H 30,31 . Besides, other accumulated phenolic acids, such as gallic acid (Compound CID: 370), reportedly have anticancer, anti-inflammatory, and hepatoprotective potential 32 . Flavonoids act as free radical scavengers, reducing agents, hydrogen donors and singlet oxygen quenchers, exhibiting high antioxidant properties 33 . Kaempferol-3-O-glucoside (Compound CID: 5282102) and catechin-5-O-glucoside (Compound CID: 44257081) are two kinds of flavonoids well-documented to have strong antioxidant activity 34 , were significantly increased and contributed to resisting oxidation during heating in the present study (Supplementary Table S4).
In our study, coumarin and lignin were all upregulated, and they are generated by phenylalanine metabolism. The phenylalanine metabolism pathway is an enzymatic reaction, and PAL is the central enzyme of phenylalanine metabolism. Under normal circumstances, PAL expression is low in plants and usually increases in response to biotic or abiotic stress like high temperature, mechanical damage, etc. Hence, it is reasonable to deduce that PAL is activated during the heat drying of Angelica dahurica, promoting phenylalanine metabolism and increasing the contents of coumarins and lignans 35 . Coumarin is well-recognized as the main pharmacological substance of Angelica dahurica. Significantly increased coumarins among the differential metabolites have certain pharmacological effects, such as scoparone (Compound CID: 8417) (Supplementary Table S4), previously established to reduce the proliferative responses of human peripheral mononuclear cells, relax smooth muscle, reduce total cholesterol and triglycerides and retard the characteristic pathomorphological changes in hypercholesterolaemic diabetic rabbits 36 . The psoralen derivative methoxsalen has a good curative effect on psoriasis and other dermatoses 37 . The observed upregulation of coumarins is consistent with the literature, and the analysis of upregulated coumarins enables the identification of the optimal drying approach for Angelica dahurica. Lignin occurs via the oxidative coupling of monolignols, synthesized by the phenylpropanoid pathway. It is an essential component of the secondary cell wall of plants, strengthening the cell structure. Accordingly, we infer that lignin accumulation is related to resisting high temperatures 38,39 .
In addition to the significant differences in the secondary metabolites generated by the phenylalanine pathway, 21 alkaloid components were significantly altered, of which 19 were upregulated. Alkaloids are formed from amino acids through a wide range of biochemical reactions. The changed alkaloids are mainly derived from tryptophan, phenylalanine, and ornithine metabolism, consistent with the differential metabolites of amino acid compounds. It can be seen that amino acid metabolism is a pathway for protein synthesis and acts as an intermediate for some metabolites, and participates in the regulation of various metabolic pathways, thereby www.nature.com/scientificreports/ affecting many physiological processes in plants. Furthermore, upregulated alkaloids such as betaine and norgalanthamine exhibit numerous pharmacological activities 40 . This study still has some limitations. It is widely acknowledged that the plant metabolome is composed of over 200,000 metabolites that control plant development, and even Arabidopsis contains 5000 metabolites 41 . Accordingly, Angelica dahurica consists of more than 995 metabolites identified in the present study. This discrepancy may be attributed to the lack of large public herbal medicine metabolite databases. Moreover, another main active ingredient of Angelica dahurica is volatile oil; however, UPLC-MS/MS analysis has limited value for detecting volatile oil. In future research, the metabolome of Angelica dahurica should be analyzed with an emphasis on volatile oil. Further studies are warranted to verify whether PAL, 4-coumarate-CoA ligase (4CL), and C4H enzymes are key in the phenylpropanoid pathway activation. Overall, this study provides a theoretical reference for the research of other substances in Angelica dahurica and corroborates that coumarin is enhanced with increased temperature within a certain range during the processing, providing novel insights on the quality of Angelica dahurica for clinical application. Liquid chromatography-mass spectrometry. The sample extracts were analyzed using a UPLC-ESI-MS/MS system (UPLC, SHIMADZU Nexera X2,(https:// www. shima dzu. com. cn/); MS, Applied Biosystems 4500 Q TRAP, (https:// www. therm ofish er. cn/ cn/ zh/ home/ brands/ appli ed-biosy stems. html). The analytical conditions were as follows, UPLC: column, Agilent SB-C18 (1.8 µm, 2.1 mm * 100 mm). The mobile phase consisted of solvent A, pure water with 0.1% formic acid, and solvent B, acetonitrile with 0.1% formic acid. The gradient program was as follows: 95:5 V/V at 0 min, 5:95 V/V at 11.0 min, 5:95 V/V at 12.0 min, 95:5 V/V at 12.1 min. Subsequently, the composition was adjusted to 95% A and 5.0% B within 1.1 min and kept for 2.9 min. The flow velocity was set as 0.35 mL per minute. The column oven was 40 °C, and the injection volume was 4 μL. The effluent was alternatively connected to an ESI-triple quadrupole-linear ion trap (QTRAP)-MS.

Materials and methods
The ESI source operation parameters were as follows: an ion source, turbo spray; source temperature 550 °C; ion spray voltage (IS) 5500 V (positive ion mode)/-4500 V (negative ion mode); ion source gas I (GSI), gas II(GSII), curtain gas (CUR) was set at 50, 60, and 25.0 psi, respectively; the collision-activated dissociation (CAD) was high. QQQ scans were acquired as MRM experiments with collision gas (nitrogen) set to medium. DP and CE for individual MRM transitions were performed with further DP and CE optimization. A specific set of MRM transitions were monitored for each period according to the metabolites eluted within this period.
Qualitative and quantitative determination of metabolites. Metabolite structure analysis was based on self-established databases HWDB. The primary and secondary spectra detected by mass spectrometry were analyzed qualitatively, and isotopic signals were removed during the analysis of some substances, including repeated signals of K + ions, Na + ions, NH 4 + ions, and fragment ions that were themselves other larger molecular weight substances repeating signal.
Metabolite quantification was carried out via the MRM mode of the QQQ mass spectrometer.

Data analysis.
A variety of statistical analysis methods were used to process the metabolic data, including principal component analysis (PCA), hierarchical cluster analysis (HCA) and orthogonal partial least squaresdiscriminant analysis (OPLS-DA). PCA was performed by the R function "prcomp" (www.r-proje ct. org). The www.nature.com/scientificreports/ HCA results of samples and metabolites were presented as heatmaps with dendrograms and were carried out by R package Complex Heatmap. For HCA, normalized signal intensities of metabolites (unit variance scaling) were visualized as a color spectrum. VIP values were extracted from the OPLS-DA result, consisting of score plots and permutation plots, generated using soft R. Identified metabolites were annotated using the KEGG Compound database (http:// www. kegg. jp/ kegg/ compo und/). Annotated metabolites were then mapped to the KEGG database (http:// www. kegg. jp/ kegg/ pathw ay. html).

Conclusion
A total of 995 metabolites were detected in TYD, TYH, TJXD, and TJXH. Among them, besides coumarin and volatile oil in Angelica dahurica, there were still other secondary metabolites with high content, pharmacological effects and application value, which can be used for future research. Furthermore, 193 differential metabolites were identified as key differential metabolites, most of which were upregulated under oven drying. The KEEG annotation and enrichment analysis showed that moderate heating could promote the phenylalanine pathway, resulting in increased coumarin content and the established potential metabolite network revealed this phenomenon. At the same time, the activation of the purine and pyrimidine pathways upregulates most primary and secondary metabolites, which are of significant value.. Nevertheless, further studies are warranted to verify whether PAL, 4-coumarate-CoA ligase (4CL), and C4H enzymes are key in the phenylpropanoid pathway activation.

Data availability
The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.